Addressing new challenges with missing data in complex epidemiological studies: methods, guidance and software

几乎所有的研究都会出现数据缺失，因此标准的分析方法可能导致不准确的结果。随着研究在设计和分析方面变得越来越复杂，这就提出了如何最好地处理缺失数据的问题。本研究的目的是开发和评估方法，使缺失的数据被适当地纳入，以确保获得有效的结论，以便为实际研究人员提供指导。

Missing data arise in almost all research studies so that standard methods of analysis can lead to inaccurate results. As research studies become more complex in their design and analysis, this raises questions around how best to handle the missing data. The aim of this research is to develop and evaluate methods that enable the missing data to be incorporated appropriately to ensure that valid conclusions are obtained in order to provide guidance for the practical researcher.